After initial implementation and deployment of software, hosted (SaaS), client-resident or some combination thereof, there are inevitably changes or upgrades that are required to keep up with changing technical and business requirements. Many of such upgrades are driven by client usage characteristics. That is, software that supports and enables many varied and configurable end-user designs and functional decisions will likely require more frequent upgrades to keep pace with these constantly changing and evolving usage characteristics. There are numerous challenges to collecting and analyzing usage data across multiple clients and further challenges to testing and implementing universal and/or client targeted upgrades to the software in an efficient and productive manner. For example, in many cases, identifying functional and detailed design decisions related to software applications is an entirely manual process. That is, users must be queried and the responses collected and analyzed manually for further use in developing upgrades. This process is both time consuming and contains inaccuracies due to human error. Further, on a client by client basis, use cases differ. Some clients rely more heavily on certain applications in a suite than others. Similarly, clients may use certain functionality within a specific application with more frequency or in a client-specific configuration. It is nearly impossible to accurately discern this level of detail about client use of software using manual processes. Accordingly, testing scope tends to either be over-inclusive or contains inaccurate use scenarios.
Accordingly, there is a need in the art for an improved system and process for identifying functional and detailed design decisions in a core software architecture across multiple applications and clients in order to accelerate the identification of testing scope for software upgrades. More particularly, an improved process is needed for precision extraction of client standard implementation decisions to accelerate the timeframe for scope confirmation in order to dictate how transactions need to be administered to replicate client usage in order to identify test case selection.